cvflann::L1< T > Struct Template Reference

#include "dist.h"

Public Types
typedef T	ElementType
typedef True	is_kdtree_distance
typedef True	is_vector_space_distance
typedef Accumulator< T >::Type	ResultType

Public Member Functions
template<typename U , typename V >
ResultType	accum_dist (const U &a, const V &b, int) const
template<typename Iterator1 , typename Iterator2 >
ResultType	operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const

Member Typedef Documentation

template<class T >

typedef T cvflann::L1< T >::ElementType

template<class T >

typedef True cvflann::L1< T >::is_kdtree_distance

template<class T >

typedef True cvflann::L1< T >::is_vector_space_distance

template<class T >

typedef Accumulator<T>::Type cvflann::L1< T >::ResultType

Member Function Documentation

template<class T >

template<typename U , typename V >

ResultType cvflann::L1< T >::accum_dist ( const U &  a, const V &  b, int    ) const

inline

Partial distance, used by the kd-tree.

template<class T >

template<typename Iterator1 , typename Iterator2 >

ResultType cvflann::L1< T >::operator() ( Iterator1  a, Iterator2  b, size_t  size, ResultType  worst_dist = -1  ) const

inline

Compute the Manhattan (L_1) distance between two vectors.

This is highly optimised, with loop unrolling, as it is one of the most expensive inner loops.

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The documentation for this struct was generated from the following file:

• flann/include/opencv2/flann/dist.h